You have to tidy your data to plot it effectively with ggplot2. There are many ways to do this, below I show two (assuming you want to plot a heatmap). Note the difference in data rearrangement between d and dd. Also, highly recommend reading the tidyr vignette and the Tidy data section in the book "R for data science" by Hadley Wickham (creator of ggplot2, tidyr and reshape2). The online version of this book is available here.

# create sample (untidy) dataset.
d <- read.table(header = TRUE, text = 
 "gene                   value_1                     value_2
  XLOC_000060           3.662330                   0.3350140
  XLOC_000074           2.568130                   0.0426299")

d
         gene value_1   value_2
1 XLOC_000060 3.66233 0.3350140
2 XLOC_000074 2.56813 0.0426299

# tidy it using tidyr package.
library(tidyr)
dd <- d %>% gather(sample, value, -gene)
dd
         gene  sample     value
1 XLOC_000060 value_1 3.6623300
2 XLOC_000074 value_1 2.5681300
3 XLOC_000060 value_2 0.3350140
4 XLOC_000074 value_2 0.0426299

# plot heatmap.
ggplot(dd, aes(x = sample, y = gene, fill = value)) + geom_tile()

# tidy it using reshape2 package.
library(reshape2)
dd <- melt(d, variable.name = "sample")
ggplot(dd, aes(x = sample, y = gene, fill = value)) + geom_tile()